Articles | Volume 12, issue 10
https://doi.org/10.5194/tc-12-3137-2018
https://doi.org/10.5194/tc-12-3137-2018
Research article
 | 
04 Oct 2018
Research article |  | 04 Oct 2018

Spatial variability in snow precipitation and accumulation in COSMO–WRF simulations and radar estimations over complex terrain

Franziska Gerber, Nikola Besic, Varun Sharma, Rebecca Mott, Megan Daniels, Marco Gabella, Alexis Berne, Urs Germann, and Michael Lehning

Related authors

The High-resolution Intermediate Complexity Atmospheric Research (HICAR v1.1) model enables fast dynamic downscaling to the hectometer scale
Dylan Reynolds, Ethan Gutmann, Bert Kruyt, Michael Haugeneder, Tobias Jonas, Franziska Gerber, Michael Lehning, and Rebecca Mott
Geosci. Model Dev., 16, 5049–5068, https://doi.org/10.5194/gmd-16-5049-2023,https://doi.org/10.5194/gmd-16-5049-2023, 2023
Short summary
Introducing CRYOWRF v1.0: multiscale atmospheric flow simulations with advanced snow cover modelling
Varun Sharma, Franziska Gerber, and Michael Lehning
Geosci. Model Dev., 16, 719–749, https://doi.org/10.5194/gmd-16-719-2023,https://doi.org/10.5194/gmd-16-719-2023, 2023
Short summary

Related subject area

Discipline: Snow | Subject: Numerical Modelling
Regime shifts in Arctic terrestrial hydrology manifested from impacts of climate warming
Michael A. Rawlins and Ambarish V. Karmalkar
The Cryosphere, 18, 1033–1052, https://doi.org/10.5194/tc-18-1033-2024,https://doi.org/10.5194/tc-18-1033-2024, 2024
Short summary
Snow cover prediction in the Italian central Apennines using weather forecast and land surface numerical models
Edoardo Raparelli, Paolo Tuccella, Valentina Colaiuda, and Frank S. Marzano
The Cryosphere, 17, 519–538, https://doi.org/10.5194/tc-17-519-2023,https://doi.org/10.5194/tc-17-519-2023, 2023
Short summary
A data exploration tool for averaging and accessing large data sets of snow stratigraphy profiles useful for avalanche forecasting
Florian Herla, Pascal Haegeli, and Patrick Mair
The Cryosphere, 16, 3149–3162, https://doi.org/10.5194/tc-16-3149-2022,https://doi.org/10.5194/tc-16-3149-2022, 2022
Short summary
Land–atmosphere interactions in sub-polar and alpine climates in the CORDEX flagship pilot study Land Use and Climate Across Scales (LUCAS) models – Part 1: Evaluation of the snow-albedo effect
Anne Sophie Daloz, Clemens Schwingshackl, Priscilla Mooney, Susanna Strada, Diana Rechid, Edouard L. Davin, Eleni Katragkou, Nathalie de Noblet-Ducoudré, Michal Belda, Tomas Halenka, Marcus Breil, Rita M. Cardoso, Peter Hoffmann, Daniela C. A. Lima, Ronny Meier, Pedro M. M. Soares, Giannis Sofiadis, Gustav Strandberg, Merja H. Toelle, and Marianne T. Lund
The Cryosphere, 16, 2403–2419, https://doi.org/10.5194/tc-16-2403-2022,https://doi.org/10.5194/tc-16-2403-2022, 2022
Short summary
Elements of future snowpack modeling – Part 1: A physical instability arising from the nonlinear coupling of transport and phase changes
Konstantin Schürholt, Julia Kowalski, and Henning Löwe
The Cryosphere, 16, 903–923, https://doi.org/10.5194/tc-16-903-2022,https://doi.org/10.5194/tc-16-903-2022, 2022
Short summary

Cited articles

Arnold, D., Schicker, I., and Seibert, P.: High-Resolution Atmospheric Modelling in Complex Terrain for Future Climate Simulations(HiRmod), Report 2010, Tech. rep., Institute of Meteorology (BOKU-Met), University of Natural Resources and Life Sciences, Vienna, Austria, 2010. a
Arthur, R., Lundquist, K. A., Mirocha, J. D., Hoch, S. W., and Chow, F. K.: High-resolution simulations of downslope flows over complex terrain using WRF-IBM, 17th Conference on Mountain Meteorology, American Meteorological Society, Paper 7.6, 18 pp., 2016. a
Beljaars, A. C. M.: The parameterization of surface fluxes in large-scale models under free convection, Q. J. Roy. Meteor. Soc., 121, 255–270, https://doi.org/10.1002/qj.49712152203, 1994. a
Bergeron, T.: On the low-level redistribution of atmospheric water caused by orography, Suppl. Proc. Int. Conf. Cloud Phys., Tokyo, 96–100, 1965. a, b
Besic, N., Figueras i Ventura, J., Grazioli, J., Gabella, M., Germann, U., and Berne, A.: Hydrometeor classification through statistical clustering of polarimetric radar measurements: a semi-supervised approach, Atmos. Meas. Tech., 9, 4425–4445, https://doi.org/10.5194/amt-9-4425-2016, 2016. a
Download
Short summary
A comparison of winter precipitation variability in operational radar measurements and high-resolution simulations reveals that large-scale variability is well captured by the model, depending on the event. Precipitation variability is driven by topography and wind. A good portion of small-scale variability is captured at the highest resolution. This is essential to address small-scale precipitation processes forming the alpine snow seasonal snow cover – an important source of water.